Proceedings of the 22nd ACM Conference on Economics and Computation最新文献

{"title":"Retrospective Search: Exploration and Ambition on Uncharted Terrain","authors":"Can Urgun, Leeat Yariv","doi":"10.2139/ssrn.3744458","DOIUrl":"https://doi.org/10.2139/ssrn.3744458","url":null,"abstract":"The search for good outcomes-be it government policies, technological breakthroughs, or a lasting purchase-takes time and effort. In this paper, we consider a continuous-time search setting. Discoveries beget discoveries and their observations are correlated over time, which we model using a Brownian motion. A searching agent makes two critical decisions: how ambitiously or broadly to search at any point, and when to cease search. Once search stops, the agent is rewarded for the best outcome observed throughout her search. We call this search process retrospective search. We fully characterize the optimal search policy. The stopping boundary takes a simple form: the agent terminates search as soon as search outcomes fall a certain fixed distance below the best-observed outcome; that fixed distance is termed the drawdown size. Search scope is chosen to minimize the expected discounted costs before either a new best-outcome is observed or search is terminated. The optimal search scope is a U- shaped function of the difference between the best outcome and the current outcome; the scope is the smallest when the difference is half of the optimal drawdown size. Both the expected best outcome and expected discounted costs are increasing in drawdown size, and the optimal drawdown size is chosen to strike a balance between the two, given the U-shaped optimal scopes. The optimal policy exhibits natural comparative statics that we explore. We also show the special features that emerge from contracting with a retrospective searcher.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134336375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Auctions of Homogeneous Goods: A Case for Pay-as-Bid","authors":"M. Pycia, Kyle Woodward","doi":"10.2139/ssrn.3865760","DOIUrl":"https://doi.org/10.2139/ssrn.3865760","url":null,"abstract":"The pay-as-bid auction is a prominent format for selling homogenous goods such as treasury securities and commodities. We analyze the optimal design of pay-as-bid auctions allowing for asymmetric information. We show that supply transparency and full disclosure are optimal in pay-as-bid, though not necessarily in uniform-price (the main alternative auction format). Pay-as-bid is revenue dominant and might be welfare dominant. Under assumptions commonly imposed in empirical work, the two formats are revenue and welfare equivalent.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133526126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Cost of Simple Bidding in Combinatorial Auctions","authors":"Vitor Bosshard, Sven Seuken","doi":"10.1145/3465456.3467609","DOIUrl":"https://doi.org/10.1145/3465456.3467609","url":null,"abstract":"We study a class of manipulations in combinatorial auctions where bidders fundamentally misrepresent what goods they are interested in. Prior work has largely assumed that bidders only submit bids on their bundles of interest, which we call simple bidding: strategizing over the bid amounts, but not the bundle identities. However, we show that there exists an entire class of auction instances for which simple bids are never optimal in BNE, always being strictly dominated by complex bids (where bidders bid on goods they are not interested in). We show this result for the two most widely used auction mechanisms:first price andVCG-nearest. We also explore the structural properties of the winner determination problem that cause this phenomenon, and we use the insights gained to investigate how impactful complex bidding manipulations may be. We find that, in the worst case, a bidder's optimal complex bid may require bidding on an exponential number of bundles, even if the bidder is interested only in a single good. Thus, this phenomenon can greatly impact the auction's outcome, and should not be ignored by bidders and auction designers alike.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128850219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtues of Patience in Strategic Queuing Systems","authors":"J. Gaitonde, É. Tardos","doi":"10.1145/3465456.3467640","DOIUrl":"https://doi.org/10.1145/3465456.3467640","url":null,"abstract":"We consider the problem of selfish agents in discrete-time queuing systems, where competitive queues try to get their packets served. In this model, a queue gets to send a packet each step to one of the servers, which will attempt to serve the oldest arriving packet, and unprocessed packets are returned to each queue. We model this as a repeated game where queues compete for the capacity of the servers, but where the state of the game evolves as the length of each queue varies, resulting in a highly dependent random process. In classical work for learning in repeated games, the learners evaluate the outcome of their strategy in each step---in our context, this means that queues estimate their success probability at each server. Earlier work by the authors [in EC'20] shows that with no-regret learners, the system needs twice the capacity as would be required in the coordinated setting to ensure queue lengths remain stable despite the selfish behavior of the queues. In this paper, we demonstrate that this myopic way of evaluating outcomes is suboptimal: if more patient queues choose strategies that selfishly maximize their long-run success rate, stability can be ensured with just e/e-1 ~1.58 times extra capacity, strictly better than what is possible assuming the no-regret property. As these systems induce highly dependent random processes, our analysis draws heavily on techniques from the theory of stochastic processes to establish various game-theoretic properties of these systems. Though these systems are random even under fixed stationary policies by the queues, we show using careful probabilistic arguments that surprisingly, under such fixed policies, these systems have essentially deterministic and explicit asymptotic behavior. We show that the growth rate of a set can be written as the ratio of a submodular and modular function, and use the resulting explicit description to show that the subsets of queues with largest growth rate are closed under union and non-disjoint intersections, which we use in turn to prove the claimed sharp bicriteria result for the equilibria of the resulting system. Our equilibrium analysis relies on a novel deformation argument towards a more analyzable solution that is quite different from classical price of anarchy bounds. While the intermediate points in this deformation will not be Nash, the structure will ensure the relevant constraints and incentives similarly hold to establish monotonicity along this continuous path.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115691453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secretaries with Advice","authors":"Paul Dütting, Silvio Lattanzi, R. Leme, Sergei Vassilvitskii","doi":"10.1145/3465456.3467623","DOIUrl":"https://doi.org/10.1145/3465456.3467623","url":null,"abstract":"The secretary problem is probably the purest model of decision making under uncertainty. In this paper we ask which advice can we give the algorithm to improve its success probability? We propose a general model that unifies a broad range of problems: from the classic secretary problem with no advice, to the variant where the quality of a secretary is drawn from a known distribution and the algorithm learns each candidate's quality on arrival, to more modern versions of advice in the form of samples, to an ML-inspired model where a classifier gives us noisy signal about whether or not the current secretary is the best on the market. Our main technique is a factor revealing LP that captures all of the problems above. We use this LP formulation to gain structural insight into the optimal policy. Using tools from linear programming, we present a tight analysis of optimal algorithms for secretaries with samples, optimal algorithms when secretaries' qualities are drawn from a known distribution, and a new noisy binary advice model.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115274024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On Social Networks that Support Learning","authors":"Itai Arieli, Fedor Sandomirskiy, Rann Smorodinsky","doi":"10.2139/ssrn.3728165","DOIUrl":"https://doi.org/10.2139/ssrn.3728165","url":null,"abstract":"Bayes-rational agents reside on a social network. They take binary actions sequentially and irrevocably, and the right action depends on an unobservable state. Each agent receives a bounded private signal about the realized state and observes the actions taken by the neighbors who acted before. How does the network topology affect the ability of agents to aggregate the information dispersed over the population by means of the private signals? Most of the literature addressing such questions assumes that the network's structure is dictated by the order in which agents take their actions. By contrast, we assume that the network preexists and the order in which agents take actions is random. Hence, the network's topology is decoupled from the order of actions in a particular decision problem. The random order leads to a novel localization phenomenon: for most of the orders, agents have a bounded radius of influence, i.e., the agent's action is unlikely to affect those who are far from him in the network. This phenomenon underlies a bunch of new effects. Global information cascades become unlikely, and networks that fail to aggregate information exhibit many local cascades. The ability of an agent to learn the right action is determined by the local structure of the network around him, and there is a local topological condition guaranteeing that the agent takes the right action no matter how well others do. Roughly speaking, the condition requires that the agent bridges a multitude of mutually exclusive social circles. Networks, where this condition is satisfied for all agents, are robust to disruptions and keep aggregating information even if a substantial fraction of the population is eliminated adversarially. The full paper can be accessed at hrefhttps://arxiv.org/pdf/2011.05255.pdf https://arxiv.org/pdf/2011.05255.pdf.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123085766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Likely Are Large Elections Tied?","authors":"Lirong Xia","doi":"10.1145/3465456.3467592","DOIUrl":"https://doi.org/10.1145/3465456.3467592","url":null,"abstract":"Understanding the likelihood for an election to be tied is a classical topic in many disciplines including social choice, game theory, political science, and public choice. The problem is important not only as a fundamental problem in probability theory and statistics, but also because of its critical roles in many other important issues such as indecisiveness of voting, strategic voting, privacy of voting, voting power, voter turn out, etc. Despite a large body of literature and the common belief that ties are rare, little is known about how rare ties are in large elections except for a few simple positional scoring rules under the i.i.d. uniform distribution over the votes, known as the Impartial Culture (IC) in social choice. In particular, little progress was made after Marchant [Mar01] explicitly posed the likelihood of k-way ties under IC as an open question in 2001. \u0000We give an asymptotic answer to the open question for a wide range of commonly-studied voting rules under a model that is much more general and realistic than i.i.d. models including IC--the smoothed social choice framework [Xia20], which was inspired by the celebrated smoothed complexity analysis [ST09]. We prove dichotomy theorems on the smoothed likelihood of ties under a large class of voting rules. Our main technical tool is an improved dichotomous characterization on the smoothed likelihood for a Poisson multinomial variable to be in a polyhedron, which is proved by exploring the interplay between the V-representation and the matrix representation of polyhedra and might be of independent interest.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114337947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Choice Screen Auctions","authors":"M. Ostrovsky","doi":"10.1145/3465456.3467526","DOIUrl":"https://doi.org/10.1145/3465456.3467526","url":null,"abstract":"Choice screen auctions have been recently deployed in 31 European countries, allowing consumers to choose their preferred search engine on Google's Android platform instead of being automatically defaulted to Google's own search engine. I show that a seemingly minor detail in the design of these auctions---whether they are conducted on a \"per appearance\" or a \"per install\" basis---plays a major role in the mix and characteristics of auction winners, and, consequently, in their expected overall market share. I also show that \"per install\" auctions distort the incentives of alternative search engines toward extracting as much revenue as possible from each user who installs them, at the expense of lowering the expected number of such users. The distortion becomes worse as the auction gets more competitive and the number of bidders increases. Empirical evidence from Android choice screen auctions conducted in 2020 is consistent with my theoretical results.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129269345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Online Assortment Optimization for Two-sided Matching Platforms","authors":"A. Aouad, D. Sabán","doi":"10.2139/ssrn.3712553","DOIUrl":"https://doi.org/10.2139/ssrn.3712553","url":null,"abstract":"Motivated by online labor markets, we consider the online assortment optimization problem faced by a two-sided matching platform that hosts a set of suppliers waiting to match with a customer. Arriving customers are shown an assortment of suppliers, and may choose to issue a match request to one of them. After spending some time on the platform, each supplier reviews all the match requests he has received and, based on his preferences, he chooses whether to match with a customer or to leave unmatched. We study how platforms should design online assortment algorithms to maximize the expected number of matches in such two-sided settings. We show that, when suppliers do not immediately accept/reject match requests, our problem is fundamentally different from standard (one-sided) assortment problems, where customers choose over a set of products. We establish that a simple greedy algorithm is 1/2-competitive against an optimal clairvoyant algorithm that knows in advance the full sequence of customers' arrivals. However, unlike related online assortment problems, no randomized algorithm can achieve a better competitive ratio, even in asymptotic regimes. To advance beyond this general impossibility, we consider structured settings where suppliers' preferences are described by the Multinomial Logit and Nested Logit choice models. We develop specialized balancing algorithms, which we call preference-aware, that leverage general information about the suppliers' choice models. In certain settings, the resulting competitive ratios are provably larger than the standard \"barrier\" of 1-1/e in the adversarial arrival model. Our results suggest that the shape and timing of suppliers' choices play critical roles in designing online two-sided assortment algorithms.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129453043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contracts under Moral Hazard and Adverse Selection","authors":"Guru Guruganesh, Jon Schneider, Joshua R. Wang","doi":"10.1145/3465456.3467637","DOIUrl":"https://doi.org/10.1145/3465456.3467637","url":null,"abstract":"In the classical principal-agent problem, a principal must design a contract to incentivize an agent to perform an action on behalf of the principal. We study the classical principal-agent problem in a setting where the agent can be of one of several types (affecting the outcome of actions they might take). This combines the contract theory phenomena of \"moral hazard\" (incomplete information about actions) with that of \"adverse selection\" (incomplete information about types). We examine this problem through the computational lens. We show that in this setting it is APX-hard to compute either the profit-maximizing single contract or the profit-maximizing menu of contracts (as opposed to in the absence of types, where one can efficiently compute the optimal contract). We then show that the performance of the best linear contract scales especially well in the number of types: if agent has n available actions and T possible types, the best linear contract achieves an O(n log T) approximation of the best possible profit. Finally, we apply our framework to prove tight worst-case approximation bounds between a variety of benchmarks of mechanisms for the principal.","PeriodicalId":395676,"journal":{"name":"Proceedings of the 22nd ACM Conference on Economics and Computation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126555562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}